Document Type
Article
Publication Date
2018
Abstract
Infrastructure managers require timely and accurate state information to diagnose, prioritize, and repair the substantial infrastructure assets supporting modern society. Challenges in obtaining sufficient information can often be attributed to inadequate data collection procedures (phone calls, paper reports, etc.) or a general lack of knowledge or ability on the part of the reporting individual to accurately convey what is actually wrong with the facility. Fortunately, modern smart-phone technology offers the potential to improve maintenance work requests by providing better geolocation and problem description accuracy. An experiment simulating real-world maintenance requests was conducted comparing smart-phones with traditional verbal work order request systems. Usefulness and description accuracy ratios revealed smartphone systems generated more useful information regardless of submitter background or experience. However, interestingly the smart-phone applications did not improve asset geolocation and actually negatively impacted the ability of maintenance personnel to accurately relocate the asset needing service. Given the ubiquitous nature of smartphone technology, the potential exists to turn any citizen into an infrastructure sensor. This study takes a step toward understanding the benefits, as well as the limitations, of the smart-phone based work order submission systems.
Source Publication
International Journal of Interactive Mobile Technologies (iJIM) (e-ISSN 1865-7923)
Recommended Citation
Guinn, V. L., Langhals, B. T., & Elshaw, J. J. (2018). Evaluating smartphones for infrastructure work order management. International Journal of Interactive Mobile Technologies, 12(8), 52–63. https://doi.org/10.3991/ijim.v12i8.9441
Comments
© 2018 The Authors.
This article is published by iJIM, licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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